AI Data Scientist

Hunter Douglas•Broomfield, CO

15h•$95,000 - $125,000•Hybrid

About The Position

Position Overview Hunter Douglas is seeking a motivated and experienced Data Scientist to join our growing AI Analytics & Digital Transformation team. This individual will play a key role in advancing Hunter Douglas’s digital and data-driven transformation by leveraging AI, machine learning, and advanced analytics to optimize operations, enhance customer experiences, and support strategic decision-making across our global business. The successful candidate will partner with business leaders across supply chain, logistics, manufacturing, sales, and customer experience to identify opportunities where AI and data science can drive measurable value — from predictive demand modeling and inventory optimization to intelligent automation and sustainability initiatives.

Requirements

Bachelor’s degree in a quantitative field (e.g., Data Science, Computer Science, Engineering, Mathematics, Statistics, Operations Research, or related).
5+ years of experience in AI/ML model development, deployment, and performance optimization in a business or industrial context.
Strong proficiency in Python, R, or SQL for data science and model development.
Demonstrated experience with machine learning frameworks and cloud platforms (AWS, Azure, GCP).
Proven ability to design and operationalize data science solutions in real-world environments.
Experience with predictive modeling, optimization, and time-series forecasting, ideally within supply chain, operations, or commercial analytics.
Knowledge of data visualization and BI tools (Power BI, Tableau, or similar).
Strong problem-solving, analytical, and communication skills.
Familiarity with version control (Git) and collaborative development practices.

Nice To Haves

Master’s in Data Science, Engineering, Statistics, or related quantitative discipline.
Experience working in manufacturing, supply chain, or consumer goods industries.
Knowledge of IoT data analytics, predictive maintenance, or computer vision in industrial applications.
Understanding of AI frameworks and automation pipelines for large-scale AI deployment.
Proven ability to manage multiple projects and deliver business impact through analytics.
Strong collaboration and communication skills to engage with diverse business teams.
Experience working with ERP and supply chain systems (SAP, Kinaxis, Oracle, etc.).

Responsibilities

Design, develop, and deploy advanced AI/ML models and algorithms that improve operational efficiency, forecasting accuracy, and decision intelligence across the Hunter Douglas supply chain.
Conduct data exploration, feature engineering, and model tuning to ensure accuracy, robustness, and business applicability.
Collaborate with business stakeholders to translate complex challenges into data-driven solutions aligned with organizational goals.
Monitor, retrain, and optimize models post-deployment to maintain high performance as data and business conditions evolve.
Apply state-of-the-art methods such as neural networks, reinforcement learning, natural language processing (NLP), and generative AI to tackle diverse business challenges.
Contribute to the AI strategy roadmap, ensuring alignment with Hunter Douglas’s digital transformation initiatives.
Work with data engineers and IT to ensure efficient data pipelines, scalable infrastructure, and model deployment.
Partner with internal and external technical teams, vendors, and consultants to implement and scale AI solutions.
Communicate findings and insights clearly to both technical and non-technical stakeholders through visualizations, presentations, and storytelling.
Stay at the forefront of AI and analytics innovation, evaluating new tools, methodologies, and technologies for potential adoption.
Collaborate with digital product and IT teams to develop and integrate AI-assisted tools and automations within Hunter Douglas’s VIBE platform and data ecosystem.
Experiment with AI coding assistants (e.g., Cursor, GitHub Copilot, OpenAI Codex) to accelerate analytics and model development and improve reproducibility.
Support the creation of custom AI copilots and prompt libraries for use in digital supply chain tools, analytics dashboards, and planning applications.
Partner with the Digital Supply Chain Leader to prototype intelligent process automation for recurring planning, logistics, quality, or operational workflows.